create powerful data visualizations · 2020. 6. 5. · four types of data visualizations conceptual...

© Corvelle Consulting 5/12/2020

Create Powerful Data Visualizations 1

Corvelle Drives Concepts to Completion

Create Powerful Data Visualizations

CGDMS Webinar

6 May 2020


Yogi SchulzBiography

❑ Founder at Corvelle Consulting

❑ Information technology related management consulting

❑ IT World Canada columnist & CBC Radio guest

❑ Former PPDM Association board member

❑ Industry presenter:– Project World - 6 years

– PMI – SAC - 10 years

– PMI - Information Systems SIG - 2 years

– PPDM Association - many years

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Topic Outline

❑ Introduction

❑ Learning objectives

❑ Powerful data visualizations:

– Understand visualizations

– Create visualizations

– Refine visualizations

– Practice and present visualizations

❑ Recommendations & actions

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Vast Data Visualization Choice

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Learning Objectives

❑ Understand design considerations that lead to powerful data visualizations

❑ Understand effective techniques to create data visualizations

❑ Understand best practicetips for presentingdata visualizations


UnderstandVisualizations

A Brief History of Data VisualizationWhen a Chart hits our Eyes

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Whirlwind Tour of theHistory of Visualization

Cave drawingsBCE

Tables & Ledgers1700’s

William Playfair1786

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Data in prose


Charles Minard 1861First Infographic

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Florence Nightingale's 'Coxcombs‘1858

❑ Pioneer hospital sanitation

❑ Meticulously gathered data

❑ Pioneer in applied statistics and visualization

❑ Nurse


Willard C. Brinton 1914First business book about visualization

❑ Rules for presenting data

❑ American consulting engineer

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Mary Eleanor Spear1952, 1969

❑ Common-sense advice

❑ Invented box plot

❑ Worked for various US government agencies

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Jacques Bertin1967

❑ Principle of expressiveness:

– Say everything you want to say —no more, no less

– Don’t mislead

❑ Principle of effectiveness:

– Use the best method available for showing your data

❑ Cartographer

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https://understandinguncertainty.org/coxcombs




Jacques BertinSeven Visual Variables

❑Position

❑Color

❑Size

❑ Shape

❑ Brightness value

❑ Orientation

❑ Texture13

Decreasingorder of

importance


Edward Tufte1983

❑ Disciplined design principles

❑ Minimalist approach

❑ Professor emeritus at Yale University

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Jock Mackinlay1986

❑ Automatically encode data with software

❑ Enable people to focus on ideas, concepts

❑ Added eighth variable to Bertin’s list: motion

❑ VP of Research and Design, Tableau Software


When a Chart hits our Eyes

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❑ Visuals aren’t read in a predictable, linear way

– Create charts spatially, from the visual outward





❑ We see first what stands out

– Whatever stands out should support idea

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❑ We see only a few visuals at once

– Plot as few visual elementsas possible







❑ We see only a few visuals at once

– Plot as few visual elements as possible

❑ We seek meaning and make connection

– Relate visual elements in a meaningful way

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❑ Visuals aren’t read in a predictable, linear way– Create charts spatially, from the visual outward

❑ We see first what stands out– Whatever stands out should support idea

❑ We see only a few visuals at once– Plot as few visual elements as possible

❑ We seek meaning and make connection– Relate visual elements in a meaningful way

❑ We rely on conventions and metaphors– Embrace deeply ingrained conventions

North

South


Example: USA Energy Resources

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AlternativeCharts


CreateVisualizations

What kind of visual communication do you want to create?

Better Visualizations in an Hour

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What kind of visual communicationdo you want to create?


What kind of visual communicationdo you want to create?

1. Is my information conceptual or data-driven?

– Conceptual information is qualitative

– Data-driven information is quantitative

2. Are my visuals meant to be declarative or exploratory?

– A declarative purpose is to make a statement

– An exploratory purpose is to look for new ideas

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Four Types of Data Visualizations

Conceptual Data-Driven

Declarative

Exploratory

Ideaillustration

Ideageneration


Four Types of Data Visualizations

Conceptual Data-Driven

Declarative

Exploratory

Everydaydataviz

Visualdiscovery

Ideaillustration

Ideageneration

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Better Visualizations in an Hour

Step 1. Preparation: 5 minutes

Step 2. Talk and listen: 15 minutes

Step 3. Sketch: 20 minutes

Step 4. Prototype: 20 minutes


Preparation: 5 minutes

❑ Create a workspace

❑ Put aside your data

❑ Write down basics as constant reminders:

– Who is in my audience?

– What is the setting?

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Talk and listen: 15 minutes

❑ Enlist a colleague

❑ Write down words, phrases, and statements


Sketch: 20 minutes

❑ Match keywords to chart types

❑ Start sketching, try out multiple visuals

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Major Visualizations Types

Visualizations Type Purpose

Comparison To compare the magnitude of measures

Change over time To display the changing trend of measures

Part-to-whole To identify the parts making up a measure total

Flow To display a flow or dynamic relations

Ranking To rank measures in an order

Spatial To display measures over spatial maps

Distribution To display the distribution of values

Correlation To show correlations between measures

Single To present single values

Narrative To tell a story with data

Filter To control report filters 33Corvelle Drives Concepts to Completion

Decision Treesfor Visualizations Types

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Visualization types in Power BIGreat article to read:


Prototype: 20 minutes

❑ Prototype approach


Example: Capital Exposure and Risk

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https://docs.microsoft.com/en-us/power-bi/visuals/power-bi-visualization-types-for-reports-and-q-and-a




Identify aValuable Message

I don’t haveanything useful

to say so I madethis pie chart.


RefineVisualizations

Refine to ImpressRefine to Persuade

Persuasion or Manipulation?


Refine to ImpressCreating that sense of good design

1. Focus on design structure and hierarchy:

– Include: title, subtitle, visual field, source line

– Align elements

American Fruit Growers

Title

Visualfield

Sourceline

39Data VisualizationsCorvelle Drives Concepts to Completion


1. Focus on design structure and hierarchy:

– Include: title, subtitle, visual field, source line

– Align elements

2. Focus on design clarity

– Make all elements support visual

– Remove ambiguity

– Use conventions and metaphors

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1. Focus on design structure and hierarchy:– Include: title, subtitle, visual field, source line– Align elements

2. Focus on design clarity– Make all elements support visual– Remove ambiguity– Use conventions and metaphors

3. Focus on design simplicity– Show only what’s needed– Minimize the number of colors


Refine to PersuadeMaking an accurate chart not enough

1. Hone main idea– Start by saying I need to convince the audience that . .

2. Make main idea stand out– Use simple design techniques to reinforce your main idea

– Emphasize main idea

3. Adjust what’s around main idea– Manipulate variables that complement main point

– Eliminate data that distracts or dilutes

– Add data to expose hidden context

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http://dilbert.com/strip/2009-03-07






Persuasion or Manipulation?

1. Truncated Y-axis– A chart removes valid value ranges from the y-axis, thereby removing

data from the visual field

2. Double Y-axis– A chart includes two vertical

scales for different data sets

3. Map– A map uses geographical boundaries

to encode values related to that location


Example: Charting the Wrong Variable

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Not so EffectiveDesign


Present andPractice Visualizations

Present to PersuadeVisual Critique


Present to PersuadePresentation Tips

❑ Show the chart and stop talking

❑ Talk about the ideas in the chart

❑ Guide the audience for unusual visual forms

❑ Use reference charts

❑ Turn off your chart when you have something important to say

– Press B for blank screen; again to return to presentation

❑ Show something simple


Present to PersuadeEngagement Tips

❑ Create tension

❑ Use time

❑ Zoom in or out

❑ Deconstruct and reconstruct

❑ Tell stories

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Example: Minimalist ApproachCommunicates Best


Communicationis never easy

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Recommendations

❑ Understand visualizations

– Enhance your understanding of visualization

❑ Create Visualizations

– Experiment in the design of visualizations

❑ Refine visualizations

– Never be satisfied with the first version

❑ Present and practice visualizations

– Invest time to practice the presentation


Never trust summary statistics alone Always visualize your data

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Questions & Discussion

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Can you help usimprove our

data visualizations?Pleasefill out

evaluationform


Create Powerful Data Visualizations

Corvelle Consulting

300, 400 - 5 Ave. S. W.

Calgary, Alberta T2P 0L6

Phone: (403) 860-5348

E-mail: [email protected]

Web: www.corvelle.com

Yogi SchulzFounder at Corvelle Consulting

Information technology related management consulting

IT World Canada columnist

Industry presenter

PPDM Association member

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create powerful data visualizations · 2020. 6. 5. · four types of data visualizations conceptual...

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